Skip to main content

A webapp to query datanommer

Project description

datagrepper

Datagrepper is a web application and JSON API to retrieve historical messages sent via Fedora Messaging. Datanommer is a seperate project and service that consumes messages from the Fedora Messaging queue and puts them in a database. These messages is what datagrepper queries.

Datagrepper is curently running in production at https://apps.fedoraproject.org/datagrepper/

Development Environment

Vagrant allows contributors to get quickly up and running with a datagrepper development environment by automatically configuring a virtual machine.

The datagrepper Vagrant environment configures configures and enables a datanommer service and database. The datanommer instance is configured to be empty when first provisioned, but to consume messages from the stage Fedora Messaging queue.

Install vagrant

To get started, run the following commands to install the Vagrant and Virtualization packages needed, and start the libvirt service:

$ sudo dnf install ansible libvirt vagrant-libvirt vagrant-sshfs vagrant-hostmanager
$ sudo systemctl enable libvirtd
$ sudo systemctl start libvirtd

Checkout and Provision

Next, check out the datagrepper code and run vagrant up:

$ git clone https://github.com/fedora-infra/datagrepper
$ cd datanommer
$ vagrant up

Interacting with your development datagrepper

After successful provisioning of the Datagrepper vagrant setup, the datagrepper web application will be accessible from your host machine's web browser at

http://datagrepper.test:5000/

Using the development environment

SSH into your newly provisioned development environment:

$ vagrant ssh

The vagrant setup also defines 4 handy commands to interact with the service that runs the datagrepper flask application:

$ datagrepper-start
$ datagrepper-stop
$ datagrepper-restart
$ dataprepper-logs

Additionally, the following commands are also available for interacting with the datanommer service:

$ datanommer-consumer-start
$ datanommer-consumer-stop
$ datanommer-consumer-restart
$ datanommer-consumer-logs

Running the tests

Datanommer is comprised of 3 seperate modules in this single repository. There is a handy script in the top directory of this repo to run the tests on all 3 modules:

$ ./runtests.sh

However, tests can also be run on a single module by invotking tox in that modules' directory. For example:

$ cd datanommer.models/
$ tox

Note, that the tests use virtual environments that are not created from scratch with every subsequent run of the tests. Therefore, when changes happen to dependencies, the tests may fail to run correctly. To recreate the virtual envrionments, run the tests commands with the -r flag, for example:

$ ./runtests.sh -r

or

$ cd datanommer.models/
$ tox -r

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

datagrepper-1.0.1.tar.gz (3.1 MB view details)

Uploaded Source

Built Distribution

datagrepper-1.0.1-py3-none-any.whl (3.1 MB view details)

Uploaded Python 3

File details

Details for the file datagrepper-1.0.1.tar.gz.

File metadata

  • Download URL: datagrepper-1.0.1.tar.gz
  • Upload date:
  • Size: 3.1 MB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.1 CPython/3.10.4

File hashes

Hashes for datagrepper-1.0.1.tar.gz
Algorithm Hash digest
SHA256 df45cc6580cc46e80705dafda8913d7b9df55bcdcac3614560d9ceee552cf577
MD5 1d07c8da569dd282e92aec9da3649054
BLAKE2b-256 f7db972cc0b5068c75fd0e48b2b2a4554b6f55326107c293a4a88513a7dfd539

See more details on using hashes here.

File details

Details for the file datagrepper-1.0.1-py3-none-any.whl.

File metadata

  • Download URL: datagrepper-1.0.1-py3-none-any.whl
  • Upload date:
  • Size: 3.1 MB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.1 CPython/3.10.4

File hashes

Hashes for datagrepper-1.0.1-py3-none-any.whl
Algorithm Hash digest
SHA256 268b521b49f1f3dc0f33117f019988206b1b1b0955ba2abfc65d6d740dad0ec5
MD5 143d660c01226ca8c6d1103b9146f960
BLAKE2b-256 d9940e8dcfd25544dbaafeb2ee20e992671aa0a311c4294f144361a7fed785bf

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page